# feature-detection-matching-algorithm

**Repository Path**: codepool_admin/feature-detection-matching-algorithm

## Basic Information

- **Project Name**: feature-detection-matching-algorithm
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-06-21
- **Last Updated**: 2024-06-21

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

#                feature detection and matching algorithm models



## Introduction		

🚀🚀This warehouse mainly uses C++ to compare traditional image feature detection and matching, and deep learning feature detection and matching algorithm models. Deep learning includes superpoint-superglue, and traditional algorithms include AKAZE, SURF, ORB, etc.

1. akaze feature point detection and matching display.

![akaze-image](./image/akaze_example.gif)

2. superpoint-superpoint feature point detection and matching display.

![akaze-video](./image/deep-learning_example.gif)

## Dependencies

All operating environments, please strictly follow the given configuration，the configuration is as follows：

OpenCV >= 3.4

CUDA >=10.2

CUDNN>=8.02

TensorRT>=7.2.3

## How to Run

1. build.

```
cd feature-detection-matching-algorithm/
mkdir build
cd build
cmake ..
make
```

2. run camera.

deep learning algorithms.

```
./IR --deeplearning --camera 0
```

traditional algorithms.

```
./IR --traditional  --camera 0
```

3. run image-pair.

deep learning algorithms.

```
./IR --deeplearning --image-pair xx01.jpg xx02.jpg
```

traditional algorithms.

```
./IR --traditional  --image-pair xx01.jpg xx02.jpg
```

## Models TRT
https://pan.baidu.com/s/1CoK_KuC42BFD-mtO-BBhHg 
Code：cb7x 

## TODO

- [ ]  Optimizing post-processing using custom TensorRT layer or Cublass.
- [ ]  Model conversion script.
- [ ]  support for FP16/INT8.

## Discussion

WeChat ID: sigma1573

Welcome to *add* WeChat(note: unit + name) and join the group discussion！

For more details, please refer to zhihu: https://zhuanlan.zhihu.com/p/518877309

## SuperPoint

Superpoint pretrained models are from [magicleap/SuperPointPretrainedNetwork.](https://github.com/magicleap/SuperPointPretrainedNetwork)

## SuperGlue

SuperGlue pretrained models are from [magicleap/SuperGluePretrainedNetwork.](https://github.com/magicleap/SuperGluePretrainedNetwork)

## Reference

```
@inproceedings{sarlin20superglue,
  author    = {Paul-Edouard Sarlin and
               Daniel DeTone and
               Tomasz Malisiewicz and
               Andrew Rabinovich},
  title     = {{SuperGlue}: Learning Feature Matching with Graph Neural Networks},
  booktitle = {CVPR},
  year      = {2020},
  url       = {https://arxiv.org/abs/1911.11763}
}
```